• Proceedings of the KSRS Conference
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• v.2
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• pp.619-622
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• 2006

Atmospheric correction is one of critical procedures to extract quantitative information related to biophysical variables from hyperspectral data. In this study, we attempted to generate the water vapor contents image from hyperspectral data itself and developed the atmospheric correction algorithm for EO-1 Hyperion data using pre-calculated atmospheric look-up-table (LUT) for fast processing. To apply the new atmospheric correction algorithm, Hyperion data acquired June 3, 2001 over Seoul area is used. Reflectance spectrums of various targets on atmospheric corrected Hyperion reflectance images showed the general spectral pattern although there must be further development to reduce the spectral noise.

• Journal of Biomedical Engineering Research
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• v.43 no.2
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• pp.71-80
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• 2022

The interaction between dual-ligand decorated particle-based delivery system and target cell under shear flow is predicted using probability model developed. We assumed the two kinds of ligand are decorated on the surface of the particle with 10% length difference. Fixed with other biophysical parameters, a study on the particle-cell interaction for the different non-specific interaction parameter is performed. To induce the firm adhesion, short ligand-receptor should be engaged. Also, it is shown that the rational design of ligand-receptor interaction, including receptor number, specific interaction parameter, kinds of ligand-receptor, etc., should be considered.

• BMB Reports
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• v.56 no.1
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• pp.32-42
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• 2023

Heart disease is one of the major life-threatening diseases with high mortality and incidence worldwide. Several model systems, such as primary cells and animals, have been used to understand heart diseases and establish appropriate treatments. However, they have limitations in accuracy and reproducibility in recapitulating disease pathophysiology and evaluating drug responses. In recent years, three-dimensional (3D) cardiac tissue models produced using tissue engineering technology and human cells have outperformed conventional models. In particular, the integration of cell reprogramming techniques with bioengineering platforms (e.g., microfluidics, scaffolds, bioprinting, and biophysical stimuli) has facilitated the development of heart-on-a-chip, cardiac spheroid/organoid, and engineered heart tissue (EHT) to recapitulate the structural and functional features of the native human heart. These cardiac models have improved heart disease modeling and toxicological evaluation. In this review, we summarize the cell types for the fabrication of cardiac tissue models, introduce diverse 3D human cardiac tissue models, and discuss the strategies to enhance their complexity and maturity. Finally, recent studies in the modeling of various heart diseases are reviewed.

• International Journal of Stem Cells
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• v.15 no.1
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• pp.60-69
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• 2022

Organoids show great potential in clinical translational research owing to their intriguing properties to represent a near physiological model for native tissues. However, the dependency of organoid generation on the use of poorly defined matrices has hampered their clinical application. Current organoid culture systems mostly reply on biochemical signals provided by medium compositions and cell-cell interactions to control growth. Recent studies have highlighted the importance of the extracellular matrix (ECM) composition, cell-ECM interactions, and mechanical signals for organoid expansion and differentiation. Thus, several hydrogel systems prepared using natural or synthetic-based materials have been designed to recreate the stem cell niche in vitro, providing biochemical, biophysical, and mechanical signals. In this review, we discuss how recapitulating multiple aspects of the tissue-specific environment through designing and applying matrices could contribute to accelerating the translation of organoid technology from the laboratory to therapeutic and pharmaceutical applications.

• Proceedings of the KSRS Conference
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• v.1
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• pp.402-405
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• 2006

Radiometric calibration of optical image data is necessary to convert raw digital number (DN) value of each pixel into a physically meaningful measurement (radiance). To extract rather quantitative information regarding biophysical characteristics of the earth surface materials, radiometric calibration is often essential procedure. A sensor detects the radiation of sunlight interacted atmospheric constituents. Therefore, the amount of the energy reaching at the sensor is quite different from the initial amount reflected from the surface. To achieve the target reflectance after atmospheric correct, an initial step is to convert DN value to at-sensor radiance. A linear model, the simplest radiometric model, is applied to averaged spectral radiance for this conversion. This study purposes to analyze the sensitivity of several factors affecting on radiance for carrying out absolute radiometric calibration of panchromatic images from KOMPSAT2 launched at July, 2006. MODTRAN is used to calculate radiance at sensor and reflectance of target is measured by a portable spectro-radiometer at the same time the satellite is passing the target for the radiometric calibration. As using different contents of materials composing of atmosphere, the differences of radiance are investigated. Because the spectral sensitivity of panchromatic images of KOMPSAT2 ranges from 500 to 900 nm, the materials causing scattering in visible range are mainly considered to analyze the sensitivity. According to the verified sensitivity, direct measurement can be recommenced for absolute radiometric calibration.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.7-14
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• 2007

Atmospheric correction is one of critical procedures to extract quantitative information related to biophysical variables from hyperspectral imagery. Most atmospheric correction algorithms developed for hyperspectral data have been based upon atmospheric radiative transfer (RT) codes, such as MODTRAN. Because of the difficulty in acquisition of atmospheric data at the time of image capture, the complexity of RT model, and large volume of hyperspectral data, atmospheric correction can be very difficult and time-consuming processing. In this study, we attempted to develop an efficient method for the atmospheric correction of EO-1 Hyperion data. This method uses the pre-calculated look-up-table (LUT) for fast and simple processing. The pre-calculated LUT was generated by successive running of MODTRAN model with several input parameters related to solar and sensor geometry, radiometric specification of sensor, and atmospheric condition. Atmospheric water vapour contents image was generated directly from a few absorption bands of Hyperion data themselves and used one of input parameters. This new atmospheric correction method was tested on the Hyperion data acquired on June 3, 2001 over Seoul area. Reflectance spectra of several known targets corresponded with the typical pattern of spectral reflectance on the atmospherically corrected Hyperion image, although further improvement to reduce sensor noise is necessary.

• Korean Journal of Agricultural and Forest Meteorology
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• v.12 no.2
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• pp.107-121
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• 2010

We conducted a sensitivity test of Joint UK Land Environment Simulator (JULES), in which the influence of biophysical parameters on the simulation of gross primary productivity (GPP) and ecosystem respiration (RE) was investigated for two typical ecosystems in Korea. For this test, we employed the whole-year observation of eddy-covariance fluxes measured in 2006 at two KoFlux sites: (1) a deciduous forest in complex terrain in Gwangneung and (2) a farmland with heterogeneous mosaic patches in Haenam. Our analysis showed that the simulated GPP was most sensitive to the maximum rate of RuBP carboxylation and leaf nitrogen concentration for both ecosystems. RE was sensitive to wood biomass parameter for the deciduous forest in Gwangneung. For the mixed farmland in Haenam, however, RE was most sensitive to the maximum rate of RuBP carboxylation and leaf nitrogen concentration like the simulated GPP. For both sites, the JULES model overestimated both GPP and RE when the default values of input parameters were adopted. Considering the fact that the leaf nitrogen concentration observed at the deciduous forest site was only about 60% of its default value, the significant portion of the model's overestimation can be attributed to such a discrepancy in the input parameters. Our finding demonstrates that the abovementioned key biophysical parameters of the two ecosystems should be evaluated carefully prior to any simulation and interpretation of ecosystem carbon exchange in Korea.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.1
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• pp.52-59
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• 1999

Vegetation canopy plays an important role in $CO_2$/$H_2$O exchange between the biosphere and the atmosphere by controlling leaf stomata. In this study, rice (Oryza sativa L.), a staple crop in Asia was investigated to formulate its single leaf model of photosynthesis and stomatal conductance. Photosynthesis and stomatal conductance were measured with a portable infrared gas analyzer system. Other plant and meteorological variables were also measured. To evaluate empirical constants in this biochemical leaf model, nonlinear least squares technique was used. The maximum catalytic activity of enzyme and the maximum rate of electron transport were $ 100\mu$㏖ $m^{-2}$ $s^{-1}$ and $140 \mu$㏖ m$^{-2}$ s$^{-1}$ (@ 35$^{\circ}C$), respectively. The empirical constants, m and b, associated with stomatal conductance model were 9.7 and $0.06 m^{-2}$ $s^{-1}$ , respectively. On a leaf scale, agreements between the modeled and the measured values of photosynthesis and stomatal conductance were on average within 20%, and the simulation of diurnal variation was also satisfactory On a canopy scale, the Simple Biosphere model(SiB2) was tested using the derived parameters. The modeled energy fluxes were compared against the micrometeorologically measured fluxes over a rice canopy. Agreements between the modeled and the measured values of net radiation, sensible heat and latent heat fluxes, and $CO_2$ flux (i.e., net canopy photosynthesis) were on average within 25%.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.4
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• pp.282-290
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• 2013

Biophysical and biochemical processes through which crops interact with the atmosphere have been simulated using land surface models and crop growth models. The Noah Multi Physics (MP) model and the CERES-Rice model, which are a land surface model, and a crop growth model, respectively, were used to simulate and compare rice growth and evapotranspiration (ET) in the areas near Haenam flux tower in Korea. Simulations using these models were performed from 2003 to 2012 during which flux measurements were obtained at the Haenam site. The Noah MP model failed to simulate the pattern of temporal change in leaf area index (LAI) after heading. The simulated aboveground biomass with the Noah MP model was underestimated by about 10% of the actual biomass. The ET simulated with the Noah MP model was as low as 21% of those with the CERES-Rice model. In comparison with actual ET measured at Haenam flux site, the root mean square error (RMSE) of the Noah MP model was 1.8 times larger than that of the CERES-Rice model. The Noah MP model seems to show less reliable simulation of crop growth and ET due to simplified phenology processes and assimilates partitioning compared with the CERES-Rice model. When ET was adjusted by the ratio between leaf biomass simulated using CERES-Rice model and Noah MP model, however, the RMSE of ET was reduced by 30%. This suggests that an improvement of the Noah MP model in representing rice growth in paddy fields would allow more reliable simulation of matter and energy fluxes.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.653-664
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• 2010

The land surface reflectance is a key parameter influencing the climate near the surface. Therefore, it must be determined with sufficient accuracy for climate change research. In particular, the characteristics of the bidirectional reflectance distribution function (BRDF) when using earth observation system (EOS) are important for normalizing the reflected solar radiation from the earth's surface. Also, wide swath satellites like SPOT/VGT (VEGETATION) permit sufficient angular sampling, but high resolution satellites are impossible to obtain sufficient angular sampling over a pixel during short period because of their narrow swath scanning. This gives a difficulty to BRDF model based reflectance normalization of high resolution satellites. The principal objective of the study is to add BRDF modeling of high resolution satellites and to supply insufficient angular sampling through identifying BRDF components from SPOT/VGT. This study is performed as the preliminary data for apply to high-resolution satellite. The study provides surface parameters by eliminating BRD effect when calculated biophysical index of plant by BRDF model. We use semi-empirical BRDF model to identify the BRD components. This study uses SPOT/VGT satellite data acquired in the S1 (daily) data. Modeled reflectance values show a good agreement with measured reflectance values from SPOT satellite. This study analyzes BRD effect components by using the NDVI(Normalized Difference Vegetation Index) and the angle components such as solar zenith angle, satellite zenith angle and relative azimuth angle. Geometric scattering kernel mainly depends on the azimuth angle variation and volumetric scattering kernel is less dependent on the azimuth angle variation. Also, forest from land cover shows the wider distribution of value than cropland, overall tendency is similar. Forest shows relatively larger value of geometric term ($K_1{\cdot}f_1$) than cropland, When performed comparison between cropland and forest. Angle and NDVI value are closely related.